Analyzing the Experience of Participating in a Mentoring Program for Academic Alert College Students Through Text Network Analysis

Abstract

The purpose of this study is to identify the effect of personal participation and interaction through activity sheets created in a course called <i>Mentoring Program for Graders</i>. In doing so, this study provides educational implications by examining the experiences of all students who participated in the programs operated in the university through the visualization of text network analysis methods and network analysis. The target audience is a total of 86 teams and 176 participants in the mentoring program for merit credits at a four-year university in G City. The program consisted of a total of 5 sessions, and participants wrote an activity report after each session. After obtaining consent for data collection and use, the contents of the activity sheets and impressions were collected, and data analysis was carried out using MAXQDA. As a result of the study, 456 codes were coded in the mentee experience, and the main keywords according to the frequency of the codes were ‘improvement of learning attitude’ and ‘enhancement of self-efficacy’. In the mentor experience, there were 411 codes, and as a result of the coding, ‘growing by helping the mentee’ and ‘pace maker’ were derived as the main keywords. Finally, a total of 1,483 codes were coded in the interaction experience, and the main keywords were ‘companionship’ and ‘steady communication’. Finally, based on the results of the code system analysis of each experience, network analysis was carried out to visually confirm Code map, and the structural analysis according to the cluster was presented. Based on these results, we proposed a plan to increase the effectiveness of the mentoring program for graders.